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GCP Data Engineer
Job in
560001, Vasanthanagar, Karnataka, India
Listed on 2026-09-26
Listing for:
Tata Consultancy Services
Full Time
position Listed on 2026-09-26
Job specializations:
-
IT/Tech
Data Engineering, Cloud Computing: Infrastructure & Operations, Data Warehousing, Database Administrator
Job Description & How to Apply Below
Overall Exp-5+
Location-Pan India
Job Requirements
* - Proficiency in programming languages:
Python, Java
- Expertise in data processing frameworks:
Apache Beam (Data Flow)
- Active experience on GCP tools and technologies like Big Query, Dataflow, Cloud Composer, Cloud Spanner, GCS, DBT etc.,
- Data Engineering skillset using Python, SQL
- Experience in ETL (Extract, Transform, Load) processes
- Knowledge of Dev Ops tools like Jenkins, Git Hub, Terraform is desirable. Should have good knowledge on Kafka (Batch/ streaming)
- Understanding of Data models and experience in performing ETL design and build, database replication using Message based CDC
- Familiarity with cloud storage solutions
- Strong problem-solving abilities in data engineering challenges
- Understanding of data security and scalability
- Proficiency in relevant tools like Apache Airflow
Core
Skills:
GCP Services : Big Query, Dataflow, Cloud Storage , Pub/Sub , Data Catalog , Data Fusion , AI Platform .
Programming : SQL, Python, Java /Scala (for Dataflow/Spark).
Data Concepts : Data Warehousing, ETL, Data Modeling, Streaming .
Tools :
Apache Beam , Docker , Kubernetes , Git , Terraform.
Key Responsibilities
* Design & Build Data Pipelines : Develop scalable data ingestion, transformation (ETL/ELT), and orchestration workflows using GCP services.
GCP Service Utilization : Implement solutions with Big Query, Dataflow , Dataproc , Cloud Storage , Pub/Sub , and Cloud Composer .
Data Integration : Connect and manage data from diverse sources (APIs, databases, files).
Optimization : Improve performance, cost-efficiency, and reliability of data processes.
Collaboration : Work with data scientists, analysts, and architects to meet data needs.
Quality & Security : Ensure data integrity, security, and compliance.
Automation : Implement CI/CD and Infrastructure as Code (IaC) using tools like Terraform.
Monitoring & Support : Maintain, monitor, and troubleshoot data workloads and systems.
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